Bio : John Skilling was awarded his PhD in radio astronomy in 1969. Through the 1970s and 1980s he was a lecturer in applied mathematics at Cambridge University, specialising in data analysis. He left to concentrate on consultancy work, originally using maximum entropy methods but moving to Bayesian methodology when algorithms became sufficiently powerful. John has been a prominent contributor to the “MaxEnt” conferences since their beginning in 1981. He is the discoverer of the nested sampling algorithm which performs integration over spaces of arbitrary dimension, which is the basic operation dictated by the sum rule of Bayesian calculus.